def _create_cells(self, cellclass, cellparams, n):
"""
Create cells in NEST.
`cellclass` -- a PyNN standard cell or the name of a native NEST model.
`cellparams` -- a dictionary of cell parameters.
`n` -- the number of cells to create
"""
# this method should never be called more than once
# perhaps should check for that
assert n > 0, 'n must be a positive integer'
n = int(n)
celltype = cellclass(cellparams)
nest_model = celltype.nest_name[simulator.state.spike_precision]
try:
self.all_cells = nest.Create(nest_model,
n,
params=celltype.parameters)
except nest.NESTError, err:
if "UnknownModelName" in err.message and "cond" in err.message:
raise errors.InvalidModelError(
"%s Have you compiled NEST with the GSL (Gnu Scientific Library)?"
% err)
raise errors.InvalidModelError(err)
def _create_cells(self):
"""
Create cells in NEST using the celltype of the current Population.
"""
# this method should never be called more than once
# perhaps should check for that
nest_model = self.celltype.nest_name[simulator.state.spike_precision]
if isinstance(self.celltype, StandardCellType):
params = _build_params(
self.celltype.native_parameters,
None,
size=self.size,
extra_parameters=self.celltype.extra_parameters)
else:
params = _build_params(self.celltype.parameter_space,
None,
size=self.size)
try:
self.all_cells = nest.Create(nest_model, self.size, params=params)
except nest.NESTError, err:
if "UnknownModelName" in err.message and "cond" in err.message:
raise errors.InvalidModelError(
"%s Have you compiled NEST with the GSL (Gnu Scientific Library)?"
% err)
raise #errors.InvalidModelError(err)
def _create_cells(self):
"""
Create cells in NEST using the celltype of the current Population.
"""
# this method should never be called more than once
# perhaps should check for that
nest_model = self.celltype.nest_name[simulator.state.spike_precision]
if isinstance(self.celltype, StandardCellType):
self.celltype.parameter_space.shape = (
self.size, ) # should perhaps do this on a copy?
params = _build_params(
self.celltype.native_parameters,
None,
size=self.size,
extra_parameters=self.celltype.extra_parameters)
else:
params = _build_params(self.celltype.parameter_space,
None,
size=self.size)
try:
self.node_collection = nest.Create(nest_model,
self.size,
params=params)
except nest.NESTError as err:
if "UnknownModelName" in err.args[0] and "cond" in err.args[0]:
raise errors.InvalidModelError(
"%s Have you compiled NEST with the GSL (Gnu Scientific Library)?"
% err)
if "Spike times must be sorted in non-descending order" in err.args[
0]:
raise errors.InvalidParameterValueError(
"Spike times given to SpikeSourceArray must be in increasing order"
)
raise # errors.InvalidModelError(err)
# create parrot neurons if necessary
if hasattr(self.celltype, "uses_parrot") and self.celltype.uses_parrot:
self.node_collection_source = self.node_collection # we put the parrots into all_cells, since this will
parrot_model = simulator.state.spike_precision == "off_grid" and "parrot_neuron_ps" or "parrot_neuron"
self.node_collection = nest.Create(
parrot_model, self.size
) # be used for connections and recording. all_cells_source
# should be used for setting parameters
self._deferred_parrot_connections = True
# connecting up the parrot neurons is deferred until we know the value of min_delay
# which could be 'auto' at this point.
if self.node_collection.local is True:
self._mask_local = np.array([True])
else:
self._mask_local = np.array(self.node_collection.local)
self.all_cells = np.array(
[simulator.ID(gid) for gid in self.node_collection.tolist()],
simulator.ID)
for gid in self.all_cells:
gid.parent = self
gid.node_collection = nest.NodeCollection([int(gid)])
if hasattr(self.celltype, "uses_parrot") and self.celltype.uses_parrot:
for gid, source in zip(self.all_cells,
self.node_collection_source.tolist()):
gid.source = source
def _create_cells(self):
"""
Create cells in NEST using the celltype of the current Population.
"""
# this method should never be called more than once
# perhaps should check for that
nest_model = self.celltype.nest_name[simulator.state.spike_precision]
if isinstance(self.celltype, StandardCellType):
self.celltype.parameter_space.shape = (
self.size, ) # should perhaps do this on a copy?
params = _build_params(
self.celltype.native_parameters,
None,
size=self.size,
extra_parameters=self.celltype.extra_parameters)
else:
params = _build_params(self.celltype.parameter_space,
None,
size=self.size)
try:
self.all_cells = nest.Create(nest_model, self.size, params=params)
except nest.NESTError as err:
if "UnknownModelName" in err.args[0] and "cond" in err.args[0]:
raise errors.InvalidModelError(
"%s Have you compiled NEST with the GSL (Gnu Scientific Library)?"
% err)
raise #errors.InvalidModelError(err)
# create parrot neurons if necessary
if hasattr(self.celltype, "uses_parrot") and self.celltype.uses_parrot:
self.all_cells_source = numpy.array(
self.all_cells
) # we put the parrots into all_cells, since this will
self.all_cells = nest.Create(
"parrot_neuron_ps", self.size
) # be used for connections and recording. all_cells_source
# should be used for setting parameters
nest.Connect(
self.all_cells_source,
numpy.array(self.all_cells),
'one_to_one',
syn_spec={'delay': simulator.state.dt}
) # for efficiency, we should defer this until after network construction,
# and use min_delay (at this point, min_delay could be 'auto')
self._mask_local = numpy.array(nest.GetStatus(self.all_cells, 'local'))
self.all_cells = numpy.array(
[simulator.ID(gid) for gid in self.all_cells], simulator.ID)
for gid in self.all_cells:
gid.parent = self
if hasattr(self.celltype, "uses_parrot") and self.celltype.uses_parrot:
for gid, source in zip(self.all_cells, self.all_cells_source):
gid.source = source
